Path Analysis of Admission and Program Achievement Variables to Predict Physician Assistant National Certifying Examination Performance: Results of a 6-Year Study.

Leslie N Woltenberg, Michael J Rudolph
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Abstract

Purpose: The primary aim of this study was the examination of relationships between students' preadmission achievement, intraphysician assistant (PA) program achievement, and Physician Assistant National Certifying Examination (PANCE) performance using path analysis regression. Second, this study explored the extent to which the theoretical model differed based on several key demographic variables: sex and undergraduate major.

Methods: This retrospective, single-institution study examined data from 2015 to 2022 (n = 322). Analysis included descriptive statistics, bivariate correlations, and path analysis using structural equation modeling to examine direct, indirect, and total effects of all predictors on the primary outcome variable, PANCE.

Results: PACKRAT-I demonstrated the largest total effect size on PANCE total score (β = .45). Total effect size on PANCE was small yet significant for prerequisite grade point average (GPA), Graduate Record Exam verbal and quantitative subscores, a comprehensive didactic cardiology examination, didactic and clinical year GPAs, and End of Rotation examination mean score (β < .25). The relationship between mean preceptor evaluation score and PANCE was nonsignificant. Subgroup analyses showed differences between female and male in the relationship between several didactic variables and preceptor evaluations. No differences were detected between groups based on undergraduate major.

Conclusion: This PANCE analysis revealed relationships among pre-PA and intra-PA performance metrics that may subsequently support data-informed strategies for programs to identify at-risk students, aid student success, and support the assessment of curriculum. Future studies should replicate the approach using a larger, multi-institution sample that examines additional preprogram and intraprogram achievement variables.

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预测国家助理医师资格考试成绩的入学和课程成绩变量路径分析:为期 6 年的研究结果。
目的:本研究的主要目的是利用路径分析回归法研究学生入学前成绩、医师助理(PA)课程成绩和医师助理国家认证考试(PANCE)成绩之间的关系。其次,本研究探讨了基于几个关键人口统计学变量(性别和本科专业)的理论模型的差异程度:这项回顾性、单一机构研究考察了 2015 年至 2022 年的数据(n = 322)。分析包括描述性统计、二元相关性和使用结构方程模型的路径分析,以检验所有预测因素对主要结果变量PANCE的直接、间接和总体影响:PACKRAT-I对PANCE总分的总效应最大(β = .45)。在先修课程平均学分绩点(GPA)、研究生入学考试言语和定量子分数、心脏病学综合教学考试、教学和临床年级平均学分绩点以及轮转结束考试平均分数方面,PANCE的总效应大小较小,但却很显著(β < .25)。实习医生评估平均分与 PANCE 之间的关系不显著。分组分析表明,女性和男性在几个教学变量和实习医生评价之间存在差异。结论:这项PANCE分析揭示了PA前和PA内绩效指标之间的关系,这些指标随后可能会支持以数据为依据的课程策略,以识别有风险的学生,帮助学生取得成功,并支持课程评估。未来的研究应该使用更大的、多机构的样本来复制这种方法,研究更多的课程前和课程内成绩变量。
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